Login / Signup

Noise Reduction in Solid-State NMR Spectra Using Principal Component Analysis.

Yasunari KusakaTakeshi HasegawaHironori Kaji
Published in: The journal of physical chemistry. A (2019)
A noise reduction method was developed for solid-state nuclear magnetic resonance spectroscopy using multivariate analysis. Principal component analysis was first applied for cross-polarization/magic angle spinning and 13C spin-lattice relaxation measurements of solid-state nuclear magnetic resonance array spectra. The contact time of cross-polarization/magic angle spinning and the delay time in spin-lattice relaxation measurements were continuously changed to obtain a series of spectra, which were used for noise reduction using principal component analysis. The noise reduction method successfully produced spectra with improved signal-to-noise ratios. This noise reduction method shortens the measurement time and allows for detection of components with minute signals.
Keyphrases
  • solid state
  • air pollution
  • density functional theory
  • magnetic resonance
  • high resolution
  • single molecule
  • room temperature
  • magnetic resonance imaging
  • molecular dynamics
  • high throughput
  • data analysis